{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  第八周进阶作业"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 使用同一相机，在两个不同的位姿分别拍摄同一个棋盘格，然后使用本质矩阵估计两次拍摄间的平移和旋转"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "先获取相机参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 设置寻找亚像素角点的参数，采用的停止准则是最大循环次数30和最大误差容限0.001\n",
    "criteria = (cv2.TERM_CRITERIA_MAX_ITER | cv2.TERM_CRITERIA_EPS, 30, 0.001)\n",
    "#棋盘格模板规格\n",
    "w = 11\n",
    "h = 8\n",
    "\n",
    "# 获取标定板角点的位置\n",
    "objp = np.zeros((h*w, 3), np.float32)\n",
    "objp[:, :2] = np.mgrid[0:w, 0:h].T.reshape(-1, 2)  # 将世界坐标系建在标定板上，所有点的Z坐标全部为0，所以只需要赋值x和y\n",
    "\n",
    "obj_points = []  # 存储3D点\n",
    "img_points = []  # 存储2D点\n",
    "\n",
    "#图片存储路径\n",
    "images = glob.glob(\"D:\\qipange\\*.jpg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n",
      "ret: 8.394111587985313\n",
      "mtx:\n",
      " [[3.58393215e+03 0.00000000e+00 2.18018064e+03]\n",
      " [0.00000000e+00 3.74637981e+03 1.99420543e+03]\n",
      " [0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
      "dist:\n",
      " [[-0.1226243   0.12999407 -0.00938165 -0.00179274 -0.11025782]]\n",
      "rvecs:\n",
      " [array([[-0.12347065],\n",
      "       [-0.02709817],\n",
      "       [ 1.58129032]]), array([[-0.53571431],\n",
      "       [-0.12132633],\n",
      "       [ 1.8403984 ]]), array([[-0.6147893 ],\n",
      "       [-0.33216904],\n",
      "       [-1.24844356]]), array([[-0.60172582],\n",
      "       [-0.24054094],\n",
      "       [-0.48363246]]), array([[-0.7203763 ],\n",
      "       [-0.3457929 ],\n",
      "       [-1.77613152]])]\n",
      "tvecs:\n",
      " [array([[ 2.85179345],\n",
      "       [-3.48875528],\n",
      "       [12.35307758]]), array([[ 4.37260404],\n",
      "       [-2.1636708 ],\n",
      "       [14.75319967]]), array([[-4.88119151],\n",
      "       [ 0.69871308],\n",
      "       [ 9.97865033]]), array([[-4.12948781],\n",
      "       [-4.01024105],\n",
      "       [12.28902975]]), array([[-3.55820266],\n",
      "       [ 2.52184739],\n",
      "       [10.05160225]])]\n"
     ]
    }
   ],
   "source": [
    "for fname in images:\n",
    "    img = cv2.imread(fname)\n",
    "    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "    size = gray.shape[::-1]\n",
    "    ret, corners = cv2.findChessboardCorners(gray, (w, h), None)\n",
    "    #print(corners)\n",
    "\n",
    "    if ret:\n",
    "        obj_points.append(objp)\n",
    "        corners2 = cv2.cornerSubPix(gray, corners, (5, 4), (-1, -1), criteria)  # 在原角点的基础上寻找亚像素角点\n",
    "        #print(corners2)\n",
    "        if [corners2]:\n",
    "            img_points.append(corners2)\n",
    "        else:\n",
    "            img_points.append(corners)\n",
    "\n",
    "        #cv2.drawChessboardCorners(img, (w, h), corners, ret)  \n",
    "        #x, y = img.shape[0:2]\n",
    "        #tempimg = cv2.resize(img,(int(y / 30), int(x / 30)))\n",
    "        #cv2.imshow('findCorners',img)\n",
    "        #cv2.waitKey()\n",
    "\n",
    "print(len(img_points))\n",
    "\n",
    "# 标定\n",
    "ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, size, None, None)\n",
    "\n",
    "np.savez('C.npz', mtx=mtx, dist=dist, rvecs=rvecs, tvecs=tvecs)\n",
    "print(\"ret:\", ret)\n",
    "print(\"mtx:\\n\", mtx) # 内参数矩阵\n",
    "print(\"dist:\\n\", dist)  # 畸变系数   distortion cofficients = (k_1,k_2,p_1,p_2,k_3)\n",
    "print(\"rvecs:\\n\", rvecs)  # 旋转向量  # 外参数\n",
    "print(\"tvecs:\\n\", tvecs ) # 平移向量  # 外参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "#设置棋盘大小\n",
    "chessboard_size = (11,8)\n",
    "# 加载相机标定的内参数、外参数矩阵\n",
    "with np.load('C.npz') as X:\n",
    "    mtx, dist, _, _ = [X[i] for i in ('mtx', 'dist', 'rvecs', 'tvecs')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_optimal_pic(path, pic_name, mtx, dist):\n",
    "\n",
    "    img2 = cv2.imread(path+str(pic_name))\n",
    "    # print(\"orgininal img_point  array shape\",img.shape)\n",
    "\n",
    "    h,  w = img2.shape[:2]\n",
    "    # print(\"pic's hight, weight: %f,  %f\"%(h, w))\n",
    "\n",
    "\n",
    "    new_mtx, roi = cv2.getOptimalNewCameraMatrix(\n",
    "        mtx, dist, (w, h), 1, (w, h))  # 自由比例参数\n",
    "\n",
    "    new_pic = cv2.undistort(img2, mtx, dist, None, new_mtx)\n",
    "\n",
    "    # 根据前面ROI区域裁剪图片\n",
    "    x,y,w,h = roi\n",
    "    new_pic = new_pic[y:y+h, x:x+w]\n",
    "    pic_new_name = str(\"opt_\")+str(pic_name)\n",
    "    new_path_name = str(path)+ pic_new_name\n",
    "    cv2.imwrite(new_path_name, new_pic)\n",
    "    print(\"##################\"+str(pic_new_name)+\"##################\")\n",
    "    print(\"get new optimal ROI picture\")\n",
    "    return pic_new_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 寻找图片角点，并且标注角点位置\n",
    "def get_corners_mat(path, pic_name, optal_or_not):\n",
    "    img = cv2.imread(str(path) + str(pic_name))\n",
    "    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)\n",
    "    ret, corners = cv2.findChessboardCorners(gray, chessboard_size, None)\n",
    "    if ret == True:\n",
    "        corners2 = cv2.cornerSubPix(gray, corners, (5, 4), (-1, -1), criteria)\n",
    "        img = cv2.drawChessboardCorners(img, chessboard_size, corners2, ret)\n",
    "\n",
    "        count = 0\n",
    "        print(\"##################\"+\"corner_\" +str(pic_name)+\"##################\")\n",
    "        for corner in corners:\n",
    "            x_label,y_label = corner[0]\n",
    "            #             print(\"corner_num:\"+str(count)+\" /location:\"+str(corner))\n",
    "            cv2.putText(img, '(%s)' % (count), (x_label,y_label), cv2.FONT_HERSHEY_COMPLEX, 0.5, (255, 255, 255), 1)\n",
    "            count = count + 1\n",
    "        if optal_or_not :\n",
    "            cv2.imwrite(path + \"corner_\" + str(pic_name), img)\n",
    "        else:\n",
    "            cv2.imwrite(path + \"orig_\" + \"corner_\" + str(pic_name), img)\n",
    "        cv2.destroyAllWindows()\n",
    "        print(\"finish find chess board\")\n",
    "    else:\n",
    "        print(\"failed to find chess board\")\n",
    "        return None\n",
    "\n",
    "    return corners"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "##################opt_left.jpg##################\n",
      "get new optimal ROI picture\n",
      "##################opt_right.jpg##################\n",
      "get new optimal ROI picture\n"
     ]
    }
   ],
   "source": [
    "# 图片去畸变和适度裁剪\n",
    "left_pic_name = get_optimal_pic(\"./qipange2/\",\"left.jpg\", mtx, dist)\n",
    "right_pic_name = get_optimal_pic(\"./qipange2/\",\"right.jpg\", mtx, dist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "##################corner_opt_right.jpg##################\n",
      "finish find chess board\n",
      "##################corner_opt_left.jpg##################\n",
      "finish find chess board\n"
     ]
    }
   ],
   "source": [
    "# 读取去畸变之后、左右相机图片\n",
    "corners_rt = get_corners_mat(\"./qipange2/\", right_pic_name, True)\n",
    "corners_lf = get_corners_mat(\"./qipange2/\", left_pic_name, True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "E:  [[-0.13121785 -0.15465509 -0.25475272]\n",
      " [ 0.02491341  0.11124241 -0.65738587]\n",
      " [ 0.38982282  0.54420716  0.02626267]]\n"
     ]
    }
   ],
   "source": [
    "# 带入参数寻找本质矩阵（使用去畸变之后的角点）\n",
    "E, mask = cv2.findEssentialMat(corners_lf, corners_rt,\n",
    "                               cameraMatrix=mtx, method=cv2.RANSAC,\n",
    "                               threshold=1, prob=0.999\n",
    "                               )\n",
    "print('E: ', E)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "retval2: 88\n",
      "####################\n",
      "rotation matrix: [[ 0.91521505 -0.20859701 -0.34477341]\n",
      " [ 0.27957883  0.94486538  0.17048489]\n",
      " [ 0.29020182 -0.25242168  0.92307432]]\n",
      "####################\n",
      "trasform matrix: [[ 0.88765391]\n",
      " [-0.33120465]\n",
      " [ 0.3199594 ]]\n",
      "####################\n",
      "sita 0 is 52.437960\n",
      "sita 1 is -11.951728\n",
      "sita 2 is -19.754061\n",
      "T's  value is  1.0\n"
     ]
    }
   ],
   "source": [
    "from math import degrees as dg\n",
    "from math import sqrt\n",
    "\n",
    "# 本质矩阵分解成R,T矩阵\n",
    "# retval2, R, t, mask = cv2.recoverPose(E, org_corners_lf, org_corners_rt, mtx)\n",
    "\n",
    "retval2, R, t, mask = cv2.recoverPose(E, corners_lf, corners_rt, mtx)\n",
    "\n",
    "print(\"retval2:\", retval2)\n",
    "print(\"##\"*10)\n",
    "print(\"rotation matrix:\", R)\n",
    "print(\"##\"*10)\n",
    "print(\"trasform matrix:\", t)\n",
    "print(\"##\"*10)\n",
    "\n",
    "dstR, _ = cv2.Rodrigues(R)\n",
    "\n",
    "sita = []\n",
    "for i in range(3):\n",
    "    sita = dg(R[0][i])\n",
    "    print(\"sita %d is %f\"%(i, sita))\n",
    "\n",
    "\n",
    "value = sqrt(t[0][0]**2 + t[1][0]**2 + t[2][0]**2)\n",
    "print(\"T's  value is \",value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# termination criteria\n",
    "criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)\n",
    "\n",
    "b = np.array([297,210])\n",
    "# 世界坐标系下的3D坐标， 棋盘格大小是（297×210mm A4纸大小）\n",
    "objp = np.zeros((np.prod(chessboard_size), 3), dtype=np.float32)\n",
    "objp[:, :2] = np.mgrid[0:chessboard_size[0],\n",
    "              0:chessboard_size[1]].T.reshape(-1, 2)*b\n",
    "\n",
    "\n",
    "# Arrays to store object points and image points from all the images.\n",
    "objpointsL = []  # 3d point in real world space\n",
    "imgpointsL = []  # 2d points in image plane.\n",
    "objpointsR = []\n",
    "imgpointsR = []\n",
    "\n",
    "images = glob.glob('./qipange2/left.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "for fname in images:\n",
    "    img = cv2.imread(fname)\n",
    "    grayL = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    # Find the chess board corners\n",
    "    ret, cornersL = cv2.findChessboardCorners(grayL, chessboard_size, None)\n",
    "    # If found, add object points, image points (after refining them)\n",
    "    if ret == True:\n",
    "        objpointsL.append(objp)\n",
    "\n",
    "        cornersL2 = cv2.cornerSubPix(grayL, cornersL, (5, 4), (-1, -1), criteria)\n",
    "        imgpointsL.append(cornersL2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4608, 3456)\n"
     ]
    }
   ],
   "source": [
    "images = glob.glob('./qipange2/right.jpg')\n",
    "\n",
    "for fname in images:\n",
    "    img = cv2.imread(fname)\n",
    "    grayR = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "    size = grayR.shape[0:2]\n",
    "    print(size)\n",
    "    # Find the chess board corners\n",
    "    ret, cornersR = cv2.findChessboardCorners(grayR, chessboard_size, None)\n",
    "\n",
    "    # If found, add object points, image points (after refining them)\n",
    "    if ret == True:\n",
    "        objpointsR.append(objp)\n",
    "\n",
    "        cornersR2 = cv2.cornerSubPix(grayR, cornersR, (5, 4), (-1, -1), criteria)\n",
    "        imgpointsR.append(cornersR2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "essisal matrix E: [[ -491.72615673   375.58517378 -2182.52316891]\n",
      " [ 1056.12860581   486.09504141 -1061.79142777]\n",
      " [ 2129.68560272   462.50207193   161.32422036]]\n",
      "##########\n",
      "rotation matrix: [[ 0.95776132 -0.15469979 -0.24240716]\n",
      " [ 0.27474936  0.74112367  0.6125753 ]\n",
      " [ 0.08488841 -0.65330214  0.75232325]]\n",
      "####################\n",
      "trasform matrix: [[ 1026.72422676]\n",
      " [-1929.07537417]\n",
      " [ 1193.70616969]]\n",
      "####################\n",
      "sita 0 is 54.875681\n",
      "sita 1 is -8.863645\n",
      "sita 2 is -13.888907\n"
     ]
    }
   ],
   "source": [
    "#俩张图片大小相近，取其中一张的大小\n",
    "retval, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, R1, T1, E1, F1 = cv2.stereoCalibrate(\n",
    "    objpointsL, imgpointsL, imgpointsR, mtx, dist,mtx, dist, (4608, 3456))\n",
    "\n",
    "print(\"essisal matrix E:\", E1)\n",
    "print(\"#\"*10)\n",
    "print(\"rotation matrix:\", R1)\n",
    "print(\"##\"*10)\n",
    "print(\"trasform matrix:\", T1)\n",
    "print(\"##\"*10)\n",
    "\n",
    "dstR1, _ = cv2.Rodrigues(R1)\n",
    "\n",
    "sita1 = []\n",
    "for i in range(3):\n",
    "    sita1 = dg(R1[0][i])\n",
    "    print(\"sita %d is %f\"%(i, sita1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从结果来看，x的移动较大，y和z轴的移动较小"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 使用一本书，在两个不同位姿拍摄，然后使用任一种匹配方法计算特征点，完成匹配，并标出匹配结果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "from matplotlib import pyplot as plt\n",
    "import matplotlib\n",
    "%matplotlib inline\n",
    "\n",
    "img_left = cv2.imread('./book/feature_left.jpg')\n",
    "img_right = cv2.imread('./book/feature_right.jpg')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sift算子\n",
    "def sift(img1, img2):\n",
    "    gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)\n",
    "    gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    maxcorners = 1000\n",
    "\n",
    "    sift = cv2.xfeatures2d_SIFT.create(nfeatures=maxcorners)\n",
    "    kp1, descriptors1 = sift.detectAndCompute(gray1,None)\n",
    "    kp2, descriptors2 = sift.detectAndCompute(gray2,None)\n",
    "\n",
    "    bfMatcher = cv2.FlannBasedMatcher()\n",
    "    matches = bfMatcher.knnMatch(descriptors1, descriptors2, k=2)\n",
    "\n",
    "    good = [[m] for m, n in matches if m.distance < 0.4 * n.distance]\n",
    "    img3 = cv2.drawMatchesKnn(img1, kp1, img2, kp2, good, None, flags=2)\n",
    "\n",
    "    plt.imshow(img3)\n",
    "    cv2.waitKey(1000)\n",
    "    cv2.imwrite(\"./picture_used/sift_matching.jpg\", img3)\n",
    "    cv2.destroyAllWindows()\n",
    "    print(\"finish sift algrithm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# SURF算子\n",
    "def SURF_detect(img1, img2):\n",
    "    gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)\n",
    "    gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    minThreashold = 1000  # hession 矩阵阈值，在这里调整精度，值越大点越少，越精准\n",
    "    surf = cv2.xfeatures2d_SURF.create(minThreashold)\n",
    "    keypoints, descriptor = surf.detectAndCompute(gray1, None)\n",
    "    keypoints2, descriptor2 = surf.detectAndCompute(gray2, None)\n",
    "\n",
    "    bfMatcher = cv2.FlannBasedMatcher()\n",
    "    matches = bfMatcher.knnMatch(descriptor, descriptor2, k=2)\n",
    "\n",
    "    good = [[m] for m, n in matches if m.distance < 0.5 * n.distance]\n",
    "    img3 = cv2.drawMatchesKnn(img1, keypoints, img2, keypoints2, good, None, flags=2)\n",
    "\n",
    "    plt.imshow(img3)\n",
    "    cv2.waitKey(1000)\n",
    "    cv2.imwrite(\"./picture_used/surf_matching.jpg\", img3)\n",
    "    cv2.destroyAllWindows()\n",
    "    print(\"finish surf algrithm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ORB_detect(img1, img2):\n",
    "    gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)\n",
    "    gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    nkeypoint = 100  # 算法在图片中找到匹配点的对数\n",
    "\n",
    "    orb = cv2.ORB.create(nkeypoint)\n",
    "\n",
    "    kp1, descriptors1 = orb.detectAndCompute(gray1, None)\n",
    "    kp2, descriptors2 = orb.detectAndCompute(gray2, None)\n",
    "\n",
    "    bf = cv2.DescriptorMatcher.create('BruteForce')\n",
    "    matches = bf.match(descriptors1, descriptors2)\n",
    "\n",
    "\n",
    "    img3 = cv2.drawMatches(img1, kp1, img2, kp2, matches, None, flags=2)\n",
    "\n",
    "    plt.imshow(img3)\n",
    "    cv2.waitKey(1000)\n",
    "    cv2.imwrite(\"./picture_used/orb_matching.jpg\", img3)\n",
    "    cv2.destroyAllWindows()\n",
    "    print(\"finish orb algrithm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "finish orb algrithm\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#sift(img_left, img_right)\n",
    "#SURF_detect(img_left, img_right)\n",
    "ORB_detect(img_left, img_right)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于版本问题，只处理了orb进行了匹配"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
